APPLICATION OF NEURAL NETWORKS TO A SCANNING PROBE MICROSCOPY SYSTEM

被引：5

作者：

HADJIISKI, L

LINNEMANN, R

STOPKA, M

OESTERSCHULZE, E

RANGELOW, I

KASSING, R

机构：

[1] Institute of Technical Physics, University of Kassel, D-34109 Kassel

来源：

THIN SOLID FILMS | 1995年 / 264卷 / 02期

关键词：

COMPUTER SIMULATION; SCANNING TUNNELING MICROSCOPY; SENSORS; TUNNELING;

D O I：

10.1016/0040-6090(95)05851-6

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

An automatic adaptation procedure based on a neural network etalon model of a scanning tunnelling microscopy system is proposed in this paper. The behaviour of the adaptive system applied to different sample surfaces and scan ranges is investigated. An improvement of the system stability and quality of the scan images is obtained.

引用

页码：291 / 297

页数：7

共 5 条

[1]

BINIG G, 1982, HELV PHYS ACTA, V55, P726

[2]

Cybenko G., 1989, Mathematics of Control, Signals, and Systems, V2, P303, DOI 10.1007/BF02551274

[3] ADAPTIVE-CONTROL OF NONLINEAR MULTIVARIABLE SYSTEMS USING NEURAL NETWORKS [J].